← Goldman Sachs Interview Insights
Start by clarifying the problem constraints (e.g., string length, character set) and then propose an efficient solution using a hash map to count character frequencies in one pass, followed by a second pass to find the first character with count 1. Discuss time and space complexity, and consider edge cases like empty string or all repeating characters.
Pro tip: Mention that you can optimize space by using a fixed-size array of 26 integers for lowercase letters, and that the two-pass approach is optimal because you must see all characters before knowing which are unique.
Ask about input size, character set (e.g., only lowercase letters), and expected output format. Confirm whether the string can be empty or contain non-lowercase characters.
Briefly mention that a naive solution would check each character against all others, resulting in O(n^2) time, which is inefficient for large inputs.
Explain that you can use a hash map (or array of size 26) to count occurrences of each character in one pass, then iterate through the string again to find the first character with count 1.
State that time complexity is O(n) and space complexity is O(1) for fixed alphabet. Discuss edge cases: empty string returns -1, no unique character returns -1, and all characters unique returns index 0.
Write clean code with meaningful variable names, and walk through a few test cases (e.g., 'leetcode' returns 0, 'loveleetcode' returns 2, 'aabb' returns -1) to verify correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This one felt simple but I spent probably two minutes just asking clarifying questions about rounding and whether ties needed to return the student ID too.
Clarify the input format and constraints, then propose a hash map solution that accumulates sum and count per student in one pass, computing averages and tracking the maximum. Discuss time and space complexity, and consider edge cases like empty input or negative scores.
Pro tip: Mention that you would handle ties or missing data explicitly, and note that a single-pass approach is optimal for large datasets, showing awareness of scalability and data integrity.
Ask about input size, data types, whether scores can be negative, and if the list is sorted. Confirm expected output format (e.g., return the highest average value or the student ID).
Use a hash map (dictionary) to store per-student sum and count, enabling O(1) updates. Alternatively, store a list of scores per student, but that uses more memory.
Iterate through the list once, updating each student's sum and count. Then iterate over the map to compute averages and track the maximum. This is O(n) time and O(k) space, where k is the number of unique students.
Consider empty input (return null or throw exception), students with no scores (should not occur if every entry has a score), and negative scores (average can be negative).
Discuss whether to compute averages on the fly or after accumulation. Mention that if the list is huge and memory is a concern, a streaming approach with a map is still optimal. Also consider if multiple passes are acceptable.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.